Brain stimulation programming

ABSTRACT

A programming system allows a user to program therapy parameter values for therapy delivered by a medical device by specifying a desired therapeutic outcome. In an example, the programming system presents a model of a brain network associated with a patient condition to the user. The model may be a graphical representation of a network of anatomical structures of the brain associated with the patient condition and may indicate the functional relationship between the anatomical structures. Using the model, the user may define a desired therapeutic outcome associated with the condition, and adjust excitatory and/or inhibitory effects of the stimulation on the anatomical structures. The system may determine therapy parameter values for therapy delivered to the patient based on the user input.

TECHNICAL FIELD

The disclosure relates to medical devices, and, more particularly,programming therapy delivered by medical devices.

BACKGROUND

Medical devices, such as electrical stimulators, may be used indifferent therapeutic applications. Medical electrical stimulationdevices, for example, may deliver electrical stimulation therapy to apatient via implanted or external electrodes to manage a patientcondition. Electrical stimulation therapy may include stimulation ofnerve, muscle, or brain tissue, or other tissue within a patient. Anelectrical stimulation system may be fully implanted within the patient.For example, an electrical stimulation system may include an implantableelectrical stimulation generator and one or more implantable leadscarrying electrodes. Alternatively, the electrical stimulation devicemay comprise a leadless stimulator. In some cases, implantableelectrodes may be coupled to an external electrical stimulationgenerator via one or more percutaneous leads or fully implanted leads.

A clinician can select values for a number of programmable stimulationparameters in order to define the electrical stimulation therapy to bedelivered to a patient. For example, the clinician may select a currentor voltage amplitude of the stimulation, and various characteristics ofthe stimulation waveform. If the stimulation is delivered in the form ofpulses, for example, the clinician may specify a pulse width and pulserate. In addition, the clinician may specify an electrode configurationused to deliver stimulation, including selected electrode combinationsand electrode polarities. A set of parameter values may be referred toas a stimulation program or a therapy program. A program group mayinclude multiple programs. In some cases, therapy can be deliveredaccording to multiple programs in a program group on a simultaneous,time-interleaved, or overlapping basis.

SUMMARY

In general, the disclosure is directed to programming stimulation thatis delivered to a brain of a patient. A medical device programmer maypresent to a user, via a user interface, a model of a brain networkassociated with a patient condition. The model of the brain network maybe a graphical representation of brain anatomical structures associatedwith the patient condition and may indicate the functional relationshipbetween the anatomical structures. The user may provide input to specifya desired effect of therapy using the presented model, where the effectof the therapy may include a therapeutic outcome. The therapeuticoutcome can include the desired efficacious therapeutic results and/orstimulation-induced side effects. For example, the user may provideinput to adjust effects of the stimulation on the anatomical structures(e.g., excitatory and/or inhibitory effects on structure, orsynchronization and/or desynchronization of two or more structures), oran activity in one structure that affects at least one other structure.The programmer may determine the stimulation parameter values fortherapy delivered to the patient via an implantable medical device (IMD)based on the therapeutic outcome indicated by the user via the userinput. In some examples, the programmer may communicate the selectedstimulation parameter values to the IMD for application to the patient.

In one example, the disclosure is directed to a method comprisingdisplaying, on a user interface of a computing device, a graphicalrepresentation of a network of interconnected anatomical structures of apatient, wherein the network includes graphical links indicatingfunctional relationships between the anatomical structures, receivinguser input via the user interface specifying at least one effect oftherapy delivered by an implantable medical device to at least one ofthe anatomical structures of the patient, and determining, with aprocessor, one or more therapy parameter values with which theimplantable medical device generates therapy based on the user input andthe functional relationships between the anatomical structures.

In another example, the disclosure is directed to a system comprising auser interface that displays a graphical representation of a network ofinterconnected anatomical structures of a patient, wherein the networkincludes graphical links indicating functional relationships between theanatomical structures, wherein the user interface receives user inputspecifying at least one effect of therapy delivered by an implantablemedical device to at least one of the anatomical structures of thepatient, and a processor that determines one or more therapy parametervalues with which the implantable medical device generates therapy basedon the user input and the functional relationships between theanatomical structures.

In another example, the disclosure is directed to a system comprisingmeans for displaying, on a user interface of a computing device, agraphical representation of a network of interconnected anatomicalstructures of a patient, wherein the network includes graphical linksindicating functional relationships between the anatomical structures,means for receiving user input via the user interface specifying atleast one effect of therapy delivered by an implantable medical deviceto at least one of the anatomical structures of the patient, and meansfor determining, with a processor, one or more therapy parameter valueswith which the implantable medical device generates therapy based on theuser input and the functional relationships between the anatomicalstructures.

In another example, the disclosure is directed to an article ofmanufacture comprising a computer-readable medium comprisinginstructions that, upon execution, cause a processor to display, on auser interface of a computing device, a graphical representation of anetwork of interconnected anatomical structures of a patient, whereinthe network includes graphical links indicating functional relationshipsbetween the anatomical structures, receive user input via the userinterface specifying at least one effect of therapy delivered by animplantable medical device to at least one of the anatomical structuresof the patient, and determine, with a processor, one or more therapyparameter values with which the implantable medical device generatestherapy based on the user input and the functional relationships betweenthe anatomical structures.

In another aspect, the disclosure is directed to an article ofmanufacture comprising a computer-readable storage medium. Thecomputer-readable storage medium comprises computer-readableinstructions for execution by a processor. The instructions cause aprogrammable processor to perform any part of the techniques describedherein. The instructions may be, for example, software instructions,such as those used to define a software or computer program. Thecomputer-readable medium may be a computer-readable storage medium suchas a storage device (e.g., a disk drive, or an optical drive), memory(e.g., a Flash memory, read only memory (ROM), or random access memory(RAM)) or any other type of volatile or non-volatile memory that storesinstructions (e.g., in the form of a computer program or otherexecutable) to cause a programmable processor to perform the techniquesdescribed herein.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example therapy systemthat includes an implantable stimulator coupled to a stimulation lead.

FIG. 2 is a functional block diagram illustrating example components ofan example implantable electrical stimulator.

FIG. 3 is a functional block diagram illustrating example components ofan example external programmer.

FIGS. 4A-4C illustrate example programmer user interfaces.

FIG. 5 illustrates an example model of a brain network associated withepilepsy.

FIG. 6 is a flow diagram of an example technique for programming amedical device.

DETAILED DESCRIPTION

A therapy system, such as an electrical stimulation system, deliverstherapy to a target tissue site in a patient in accordance with one ormore therapy programs, where each therapy program defines one or moretherapy parameter values. The therapy parameter values can be selectedbased on various factors, such as the type of therapy delivery member(e.g., a lead comprising electrodes, a catheter comprising a fluiddelivery port, or a leadless stimulator that does not include a separatetherapy delivery member), medical device or other hardware included inthe therapy system, the target tissue site for the therapy delivery, theproximity of the therapy delivery member to the target tissue site, andthe like. In some examples, therapy parameter values can be selected(e.g., initially selected or, if the parameter values have already beenselected, modified) after implantation of the therapy delivery member ina patient. In some cases, it may be useful to modify therapy parametervalues after implantation of the therapy delivery member in the patientbecause the actual implant site of the therapy delivery member withinthe patient may not correspond exactly to the intended implant locationor the therapy delivery member has shifted or migrated from its implantlocation. Thus, if therapy parameter values are selected prior toimplantation of the therapy delivery member in the patient, the selectedtherapy parameter values may not provide the expected therapeuticeffects because, for example, the therapy delivery member is implantedat a different tissue site.

In addition, in some cases, for a given patient condition state, it canbe relatively difficult to predetermine useful therapy parameter valuesprior to implantation of the therapy delivery member in the patient.Further, if therapy parameter values are preselected for a patient basedon patient non-specific physiological information (e.g., referenceanatomical image or an anatomical atlas not specific to the patient),modification to the therapy parameter values may be desirable afterimplantation of the therapy delivery member in the patient because theactual anatomical structures of the patient may differ in size,location, or another characteristic relative to the patient non-specificdata.

In some programming systems, a user (e.g., a clinician) doctor whoprograms the implanted medical device (IMD) that delivers stimulation tothe target region can modify the stimulation therapy by manipulatingsingle variables, such as values of one or more stimulation parameters.Some stimulation parameters that can be adjusted include electrodeconfiguration, current or voltage amplitude, and, in the case ofstimulation pulses, pulse rate and pulse width. The user can adjustvalues for one or more stimulation parameter values at a time in a trialand error manner until a desired therapeutic outcome is achieved.

Due to the complexity of some therapy systems, modifying therapy byadjusting one or more individual therapy parameter values at a time canbe relatively burdensome and time consuming. In addition, the complexityof some therapy systems can result in relatively long programmingsessions, burdening the patient, and possibly affecting therapeuticefficacy if effective stimulation parameters are not achieved. Forexample, some therapy systems deliver therapy according to two or moreinterleaved therapy programs and/or have the ability to deliversimultaneous pulses of differing amplitudes (e.g., current steering) totarget several conditions and target anatomical structures. Deliveringtherapy according to multiple therapy programs (e.g., parameter sets)introduces additional programming considerations that may worksynergistically to achieve a desired therapeutic outcome, which theclinician may have difficulty fully understanding or appreciating.

In addition, some therapy systems include sophisticated electrodedesigns, such as complex electrode geometries with axially-segmentedcontacts, and the ability to sense local field potentials and the powerspectra of sensed physiological signals at different electrodelocations. Some therapy systems also include the ability to implantelectrodes in distinct structures of the brain and stimulate thestructures substantially simultaneously. This can be achieved usingleads with non-uniformly spaced electrodes or by systems that supportmultiple leads, each with a set of connected or independentlyactivatable electrodes. For example, an example therapy system maysupport four leads such that the system can simultaneously stimulateboth the subthalamic nucleus (STN) and the external/internal globuspallidus (GPe/GPi) of a given hemisphere of the brain. Selectingstimulation parameter values for the more electrode designs (e.g., anelectrode configuration more complex than a simple linear array ofelectrodes) or the therapy systems that deliver stimulation to multipleanatomical structures of the brain substantially simultaneously may berelatively difficult due to the synergy that may result from thedifferent therapy parameters and other considerations.

In one method of selecting stimulation therapy parameter values, a userselects one or more stimulation parameter values based on a predictionof the volume of tissue activated by a given stimulation configurationfor a specific patient's anatomy. This method abstracts the programmingissues, and allows the user to better visualize the impact of parameterchanges, which can help expedite the therapy parameter selection.Additionally, this method may allow the user to directly select andmanipulate the volume of tissue activation. However, this method ofparameter selection may not utilize an exact relationship between thevolume of tissue activated and the desired therapeutic outcome in thepatient. For example, in cases in which stimulation may either excite orinhibit activity in the tissue, depending on the specific stimulationparameters used (e.g., stimulation rates, implant locations ofelectrodes), the volume of activation is useful in making the processmore efficient, but it may not be sufficient to avoid the issue ofoptimization of parameters, one at a time. Activity can include, forexample, electrical activity or hemodynamic activity.

Devices, systems, and techniques described herein are directed toprogramming a medical device based on user input that specifies at leastone effect of therapy delivered by a medical device to one or moreanatomical structures in a brain of a patient. The effect of therapy canindicate, for example, an outcome associated with stimulating at leastone structure of the brain. The user input may, for example, manipulatethe activity of anatomical structures of a brain network. The anatomicalstructures of the brain network may be functionally related to oneanother via neurological pathways in a manner that causes activitywithin one anatomical structure of the network to be influenced byactivity within another anatomical structure of the network. Aspects ofthe devices, systems, and techniques described herein may decrease theburden on the user in selecting stimulation therapy parameter values fora patient compared to some conventional programming techniques, and mayimprove efficacy of therapy for a given lead location and a givenpatient anatomy.

In examples described herein, a user selects one or more stimulationtherapy parameter values by specifying the desired therapeutic effect ofthe therapy via a user interface that graphically depicts theinteraction of anatomical structures of the brain. In an example, amedical device programmer presents a model of a brain network associatedwith a patient condition to the user. The model may resemble a networkdiagram, and can graphically depict representations of brain anatomicalstructures that are functionally connected, such that stimulation of onepart of the brain network in one anatomical structure may generateexcitatory and/or inhibitory effects on other anatomical structureswithin the brain network. For example, stimulation of one brainstructure may have an excitatory effect on another structure, or causethe activity (e.g., electrical activity or hemodynamic activity) in theother brain structure to increase. In another example, stimulation ofone brain structure may have an inhibitory effect on another structure,or cause the activity (e.g., electrical activity or hemodynamicactivity) in the other brain structure to decrease. The model of thebrain network may include graphical links between the graphicalrepresentations of the anatomical structures, where the graphical linksvisually indicate a functional relationship between the anatomicalstructures. In some examples, stimulation of one or more brainanatomical structure may result in synchronization or desynchronizationbetween two or more brain structures. Two structures may be consideredto be synchronized if their activity (e.g., electrical activity orhemodynamic activity) is correlated, or the peaks in a given spectralband of a bioelectrical brain signal representing their behaviors arerelatively highly correlated (e.g., peaks of a spectral band of twobrain structures occur at approximately the same time or with aconsistent leading or lagging phase behavior). Two structures may beconsidered to be desynchronized if their activity is not correlated, orthe peaks in a given spectral band representing their behavior are notcorrelated (e.g., the activity in one structure is not predictable giventhe activity in another structure). In some examples, synchronization oftwo or more structures may be desirable. In other examples,desynchronization of two or more structures may be desirable. Forexample, in epilepsy, synchronization of normally desynchronized brainstructures may indicate the presence of, or predict a condition orsymptom associated with epilepsy (e.g., a seizure). In this example,stimulation may be delivered to one or more of the brain structures tohelp desynchronize the activity of the two brain structures, therefore,mitigating or even preventing the seizure.

Using the model, the user may define a desired therapeutic outcome oradjustment to characteristics (e.g., tremor for patients withParkinson's disease) associated with the patient condition by adjustingactivity in one or more anatomical structure of the brain networkrepresented by the model by interacting with the user interface. Theprogrammer can then determine stimulation therapy parameter values thatmay achieve the desired therapeutic effect of the stimulation therapy.In some examples, the programmer may store the selected stimulationtherapy parameter values and/or may communicate the parameter values tothe IMD for stimulation therapy delivery.

The examples of this disclosure discuss utilizing a stimulator withleads, for illustration. Aspects of this disclosure may be applicable toleadless stimulators and other types of medical devices capable ofproviding stimulation therapy.

FIG. 1 is a conceptual diagram illustrating an example therapy system 2including an implantable electrical stimulator 34 that deliversstimulation therapy to patient 6. Patient 6 ordinarily, but notnecessarily, will be a human. In the example shown in FIG. 1, therapysystem 2 may be referred to as a deep brain stimulation (DBS) systembecause implantable electrical stimulator 4 delivers electricalstimulation therapy directly to tissue within brain 16, such as underthe dura matter of brain 16. In addition to or instead of deep brainsites, implantable electrical stimulator 4 may deliver electricalstimulation to target tissue sites on a surface of brain 16, such asbetween the patient's cranium and the dura mater of brain 16 (e.g., thecortical surface of brain 16). Implantable stimulator 4 can delivertherapy to brain 16 of patient 6 to treat any of a variety of patientconditions, such as neurological disorders or diseases. Exampleneurological disorders may include depression, dementia,obsessive-compulsive disorder, and movement disorders, such asParkinson's disease, spasticity, epilepsy, and dystonia. DBS may also beuseful for treating other patient conditions, such as migraines,obesity, and mood disorders (e.g., depression or an anxiety disorder).

Implantable electrical stimulator 4 delivers electrical stimulation topatient 6 via one or more implantable electrodes 11. The implantableelectrodes 11 may be deployed on one or more implantable medical leads,such as implantable medical lead 10 with lead segments 12A and 12B, and,in some cases, on a housing 14 of the medical device. The electricalstimulation may be in the form of controlled current or voltage pulsesor substantially continuous waveforms. Various parameters of the pulsesor waveforms may be defined by one or more therapy programs (alsoreferred to as “stimulation programs” in the case of stimulationtherapy). The pulses or waveforms may be delivered substantiallycontinuously or in bursts, segments, or patterns, and may be deliveredalone or in combination with pulses or waveforms defined by one or moreother stimulation programs. Although FIG. 1 shows a fully implantablestimulator 4, techniques described in this disclosure may be applied toexternal stimulators having electrodes deployed via percutaneouslyimplantable leads with a patch electrode or other indifferent electrodeattached externally to serve as the reference electrode. In addition, insome cases, implantable electrodes may be deployed on a leadlessstimulator, in which case stimulator 4 may not be coupled to lead 10.

In the example illustrated in FIG. 1, implantable stimulator 4 isimplanted within a subcutaneous pocket in a clavicle region of patient6. Stimulator 4 generates programmable electrical stimulation, e.g., acurrent or voltage waveform, or current or voltage pulses, and deliversthe stimulation via an implantable medical lead 10 carrying an array ofimplantable stimulation electrodes 11. In some cases, multipleimplantable leads may be provided. In the example of FIG. 1, a distalend of lead 10 is bifurcated and includes two lead segments 12A and 12B(collectively “lead segments 12”). Lead segments 12A and 12B eachinclude a set of electrodes forming part of the array of electrodes 11.In various examples, lead segments 12A and 12B may each carry four,eight, twelve, sixteen, or more electrodes, although system 2 caninclude any suitable number of electrodes on any suitable number ofleads. In the example shown in FIG. 1, each lead segment 12A, 12Bincludes four electrodes, which are configured as ring electrodes atdifferent axial positions near the distal ends of the lead segments.Throughout the remainder of this disclosure, for purposes of simplicity,the disclosure may generally refer to electrodes carried on “leads”rather than “lead segments.”

FIG. 1 further depicts a housing, or can, electrode 13. Housingelectrode 13 may be formed integrally with an outer surface ofhermetically-sealed housing 14 of implantable stimulator 4 (alsoreferred to in this disclosure as implantable medical device (IMD) 4),or otherwise coupled to housing 14. In one example, housing electrode 13may be described as an active, non-detachable electrode on the surfaceof the IMD. In some examples, housing electrode 13 is defined by anuninsulated portion of an outward facing portion of housing 14 of IMD 4.Other divisions between insulated and uninsulated portions of housing 14may be employed to define two or more housing electrodes, which may bereferred to as case or can electrodes. In some examples, housingelectrode 13 comprises substantially all of housing 14, one side ofhousing 14, a portion of the housing 14, or multiple portions of housing14. In other examples, electrode 13 may be formed by an electrode on adedicated short lead extending from housing 14. As a furtheralternative, housing electrode 13 could be provided on a proximalportion of one of the leads carrying electrodes 11. The proximal portionmay be closely adjacent to housing 14, e.g., at or near a point at whichlead 10 is coupled to the housing, such as adjacent to a lead connectionheader 8 of the housing. In another example, a patch electrode or otherindifferent electrode may be attached externally to serve as thereference electrode.

In some examples, lead 10 may also carry one or more sense electrodes topermit implantable stimulator 4 to sense electrical signals from patient6. Some of the stimulation electrodes may be coupled to function asstimulation electrodes and sense electrodes on a selective basis. Inother examples, implantable stimulator 4 may be coupled to one or moreleads which may or may not be bifurcated. In such examples, the leadsmay be coupled to implantable stimulator 4 via a common lead extensionor via separate lead extensions.

A proximal end of lead 10 may be both electrically and mechanicallycoupled to header 8 on implantable stimulator 4, either directly orindirectly via a lead extension. Conductors in the lead body of lead 10may electrically connect stimulation electrodes located on lead segments12 to implantable stimulator 4. Lead 10 traverses from the implantregion of implantable stimulator 4 along the neck of patient 6 tocranium 18 of patient 6 to access brain 16. Lead segments 12A and 12Bare implanted within the right and left hemispheres, respectively, inorder to deliver electrical stimulation to one or more structures ofbrain 16, which may be selected based on the patient condition. Thedisclosure is not limited to the configuration of lead 10 shown in FIG.1, or to the delivery of DBS or CS therapy.

Lead segments 12A, 12B may be implanted within a desired location ofbrain 16 through respective holes in cranium 18. Lead segments 12A, 12Bmay be placed at any location within brain 16 such that the electrodes11 located on lead segments 12A, 12B are capable of providing electricalstimulation to a target therapy delivery site within brain 16. In thecase of movement disorders, example locations for lead segments 12A, 12Bwithin brain 16 may include the pedunculopontine nucleus (PPN),thalamus, basal ganglia structures (e.g., globus pallidus, substantianigra, subthalamic nucleus), zona inserta, fiber tracts, lenticularfasciculus (and branches thereof), ansa lenticularis, and/or the Fieldof Forel (thalamic fasciculus). In the case of migraines, lead segments12 may be implanted to provide stimulation to the visual cortex of brain16 in order to reduce or eliminate migraine headaches afflicting patient6. In general, the target therapy delivery site may depend upon thepatient condition being treated.

In the example shown in FIG. 1, electrodes 11 of lead segments 12 arering electrodes. Ring electrodes are relatively simple to program andare capable of delivering an electrical field to any tissue adjacent tolead segments 12. In other examples, electrodes 11 of lead segments 12may have different configurations. For example, electrodes 11 of leadsegments 12 may have a complex electrode array geometry that is capableof producing shaped electrical fields. The complex electrode arraygeometry may include multiple electrodes (e.g., partial ring orsegmented electrodes) around the outer perimeter of each lead segment12A, 12B, rather than one ring electrode. In this manner, electricalstimulation may be directed in a specific direction from lead segments12 to enhance therapy efficacy and reduce possible adverse side effectsfrom stimulating a large volume of tissue. In alternative examples, oneor both lead segments 12 may have shapes other than elongated cylindersas shown in FIG. 1. For example, lead segments 12 may be paddle leads,spherical leads, bendable leads, or any other type of shape effective intreating patient 6.

In the example shown in FIG. 1, therapy system 2 includes clinicianprogrammer 20 and patient programmer 22. Clinician programmer 20 may bea computing device that permits a clinician to program stimulationtherapy delivered by stimulator 4 via a user interface, e.g., usinginput keys and a display. For example, using clinician programmer 20,the clinician may specify stimulation parameter values, i.e., createtherapy programs, for use in delivery of stimulation therapy bystimulator 4. Clinician programmer 20 may support telemetry (e.g., radiofrequency (RF) telemetry) with implantable stimulator 4 to downloadprograms and, optionally, upload operational or physiological datastored by implantable stimulator 4. In this manner, the clinician mayperiodically interrogate implantable stimulator 4 with clinicianprogrammer 20 to evaluate efficacy based on the stored physiologicaldata and, if necessary, modify the programs or create new programs. Insome examples, clinician programmer 20 transmits programs to patientprogrammer 22 in addition to or instead of implantable stimulator 4.

In some examples, patient programmer 22 may serve as the clinicianprogrammer. In some examples, a programmer can be a dedicated computingdevice or it can be any suitable general purpose computing device thatcan be used for programming purposes. In other examples, a programmermay be a device that serves as a client device to a workstation orserver infrastructure connected via a network, where the workstation orserver supplies computational capability (e.g., to determine one or moretherapy parameter values based on user input indicating a desiredtherapeutic effect of stimulation therapy), communicates results to theprogrammer, and the programmer displays the results at a point of use.

Like clinician programmer 20, patient programmer 22 may be a handheldcomputing device. Patient programmer 22 may also include a display andinput keys to allow patient 6 to interact with patient programmer 22 andimplantable stimulator 4. In this manner, patient programmer 22 providespatient 6 with a user interface for control of the stimulation therapydelivered by implantable stimulator 4. For example, patient 6 may usepatient programmer 22 to start, stop or adjust electrical stimulationtherapy. In particular, patient programmer 22 may permit patient 6 toadjust stimulation parameters of a program such as duration, current orvoltage amplitude, pulse width and pulse rate. Patient 6 may also selecta therapy program, e.g., from among a plurality of stored therapyprograms, as the present program to control delivery of stimulation byimplantable stimulator 4. In one example, patient programmer 22 may havepermissions associated with the therapy programs it controls, and maygive patient 6 the ability to change certain parameter values and/orprograms.

A user can interact with clinician programmer 20, patient programmer 22or another computing device to define stimulation therapy parametervalues for generation by stimulator 4 and delivery to a target tissuesite within brain 16 of patient 12 by one or more leads 10. While thedisclosure primarily refers to a user interface presented by clinicianprogrammer 20 for programming stimulation therapy delivered bystimulator 4, in other examples, the techniques described herein can beperformed by patient programmer 22 or another computing device. Thus,the description of clinician programmer 20 can also be relevant topatient programmer 22 or another computing device.

In some examples described herein, clinician programmer 20 generates anddisplays a graphical user interface that presents a high level model ofa brain network that includes functionally related anatomical structuresof the brain associated with a patient condition, where stimulationapplied to one anatomical structure of the network affects one or moreother anatomical structures of the network and the characteristicsassociated with the patient condition (e.g., one or more symptoms,presence/absence/severity of side effects such as paresthesias, blurredvision, cognitive deficits, and the like). The user can select at leastone effect of therapy delivered by stimulator 4 to one or moreanatomical structures within the brain network by interacting with theuser interface. The effect of therapy may be, for example, a desiredtherapeutic outcome for the stimulation therapy delivered to patient 6.For example, the user can adjust activity in the one or more anatomicalstructure of the brain network represented by the model by interactingwith the user interface. The activity may be, for example, bioelectricalbrain signal activity or hemodynamic activity. Examples of bioelectricalbrain signals include, but are not limited to, electrical signalsgenerated from local field potentials (LFP) sensed within one or morestructures of brain 28, such as an electroencephalogram (EEG) signal, oran electrocorticogram (ECoG) signal. LPFs, however, may include abroader genus of electrical signals within brain 28 of patient 12.Hemodynamic activity within a brain structure may be indicated by, forexample, blood flow, blood pressure, or blood volume within the brainstructure.

In response to receiving user input indicating a desired therapeuticoutcome, clinician programmer 20 can select the stimulation parametervalues that may achieve the user-selected therapeutic outcome. Forexample, clinician programmer 20 can translate one or more user-selectedtherapeutic outcomes into a subset of electrodes 11 for deliveringelectrical stimulation therapy to a patient and the values of thestimulation signal delivered via the subset of electrodes 11. In thisway, the user can select one or more stimulation parameter values byselecting a desired therapeutic outcome via the user interface ofclinician programmer 20.

In one example, clinician programmer 20 presents a model of a brainnetwork associated with a patient condition and receives input from auser that indicates the desired effect on certain structures of thebrain network, where the structures may represent respective structuresof the brain. In one example, clinician programmer 20 may allow the userto utilize a user interface to change the inhibitory and/or excitatoryeffects on brain structures and/or to induce synchronization ordesynchronization between two or more brain structures within the modelof the brain network, and the stimulation therapy parameter values maybe adjusted accordingly to achieve user-specified effects.

In one example, implantable stimulator 4 delivers stimulation therapyaccording to the stimulation therapy parameter values selected byprogrammer 20 based on user input. The therapy parameter values may beorganized as a therapy program or as a group of therapy programs. Eachtherapy program may include respective values for each of a plurality oftherapy parameters, such as respective values for each of current orvoltage amplitude, pulse width, pulse shape, pulse rate and electrodeconfiguration (e.g., electrode combination and polarity). In someexamples, implantable stimulator 4 delivers stimulation according to agroup of therapy programs at a given time. Implantable stimulator 4 mayinterleave pulses or other signals according to the different programsof a program group, e.g., cycle through the programs, to simultaneouslytreat different symptoms or different body regions, or provide acombined therapeutic effect.

Implantable stimulator 4, clinician programmer 20, and patientprogrammer 22 may communicate via cables or a wireless communication, asshown in FIG. 1. Clinician programmer 20 and patient programmer 22 may,for example, communicate via wireless communication with implantablestimulator 4 using RF telemetry techniques known in the art or otherstandard communication protocols such as, for example, Bluetooth®.Clinician programmer 20 and patient programmer 22 also may communicatewith each other using any of a variety of wired or wirelesscommunication techniques, such as RF communication according to the802.11 or Bluetooth® specification sets, infrared communication, e.g.,according to the IrDA standard, or other standard or proprietarytelemetry protocols. Each of clinician programmer 20 and patientprogrammer 22 may include a transceiver to permit bi-directionalcommunication with implantable stimulator 4.

Although the disclosure generally refers to implantable stimulators forpurposes of illustrations, techniques described in this disclosure alsomay be used with other types of implantable medical devices and forconditions associated with other organs or parts of a patient's body.Accordingly, description of implantable stimulators is provided forpurposes of illustration and should not be considered limiting of thetechniques as broadly described in this disclosure.

FIG. 2 is a functional block diagram illustrating various components ofan example implantable stimulator 34. Implantable stimulator 34 is anexample of implantable stimulator 4 shown in FIG. 1. In the exampleshown in FIG. 2, implantable stimulator 34 includes processor 50, memory52, power source 54, telemetry module 56, antenna 57, sensing module 58,and stimulation generator 60. Implantable stimulator 34 is also shown inFIG. 2 coupled to each of the electrodes 48A-48Q (collectively“electrodes 48”) via a respective conductor. In some examples, two ormore electrodes 48 may be coupled to stimulation generator 60 via acommon conductor. Electrodes 48A-48P are implantable and may be deployedon one or more implantable leads. With respect to FIG. 1, lead segments12A and 12B may carry electrodes 48A-48H and electrodes 48I-48P,respectively. In some cases, one or more additional electrodes may belocated on or within the housing of implantable stimulator 34, e.g., toprovide a common or ground electrode or a housing anode. In the exampleof FIG. 1, a lead or lead segment carries eight electrodes to provide an2×8 electrode configuration (e.g., two leads with 8 electrodes each oran array of electrodes comprising two columns and eight rows), providinga total of sixteen different electrodes. The leads may be detachablefrom a housing associated with implantable stimulator 34, or be fixed tosuch a housing.

In other examples, a therapy system can include different electrodeconfigurations comprising a single lead, two leads, three leads, or morethan three leads. In addition, electrode counts on leads may vary andmay be the same or different from lead to lead. Examples of otherconfigurations include one lead with eight electrodes (1×8), one leadwith 12 electrodes (1×12), one lead with 16 electrodes (1×16), two leadswith four electrodes each (2×4), three leads with four electrodes each(3×4), three leads with eight electrodes each (3×8), three leads withfour, eight, and four electrodes, respectively (4-8-4), two leads with12 or 16 electrodes (2×12, 2×16), or other configurations. In addition,in other examples, stimulation generator 60 may deliver stimulation topatient 6 via electrodes on a paddle lead, which can have apaddle-shaped distal end that may include multiple columns and rows ofelectrodes. Different electrodes are selected to form electrodecombinations. Polarities are assigned to the selected electrodes to formelectrode configurations.

Memory 52 may store instructions for execution by processor 50,stimulation therapy data and/or other information regarding therapy forpatient 6. Processor 50 may control stimulation generator 60 to generateand deliver stimulation according to a selected one or more of aplurality of therapy programs or program groups stored in memory 52.Each stored therapy program defines a particular set of electricalstimulations parameters, such as a stimulation electrode combination orconfiguration, current or voltage amplitude, frequency (e.g., pulse ratein the case of stimulation pulses), and pulse width. Memory 52 mayinclude any electronic data storage media, such as random access memory(RAM), read-only memory (ROM), electronically-erasable programmable ROM(EEPROM), flash memory, or the like. Memory 52 may store programinstructions that, when executed by processor 50, cause the processor toperform various functions ascribed to processor 50 and implantablestimulator 34 in this disclosure.

In some examples, information stored by memory 52 may includeinformation regarding therapy that patient 6 had previously received orinformation regarding a current therapy regimen. Storing both historicaland current therapy information may be useful for subsequent therapysuch that, for example, a clinician may retrieve the stored informationto determine the therapy applied to the patient during a previoustherapy session. The information stored in memory 52 may also include,for example, information regarding the brain structures associated withpatient condition and the corresponding stimulation therapy programdefined by stimulation therapy parameter values, where applying thestimulation therapy program helps control the anatomical structures ofthe brain to achieve a desired therapeutic outcome for the associatedpatient condition.

Processor 50 may include one or more microprocessors, digital signalprocessors (DSPs), application-specific integrated circuits (ASICs),field-programmable gate arrays (FPGAs), or other digital logiccircuitry. Functions attributed to processors described herein may beembodied in a hardware device via software, firmware, hardware, or anycombination thereof. Processor 50 controls operation of implantablestimulator 34, e.g., controls stimulation generator 60 to generate anddeliver stimulation therapy according to a selected therapy program orgroup of therapy programs retrieved from memory 52. For example,processor 50 may control stimulation generator 60 to deliver electricalsignals, e.g., as stimulation pulses or continuous waveforms, withcurrent or voltage amplitudes, pulse widths (if applicable), and ratesspecified by one or more stimulation programs. Processor 50 may alsocontrol stimulation generator 60 to selectively deliver the stimulationvia subsets of electrodes 48, also referred to as electrodecombinations, and with polarities specified by one or more programs.

Upon selection of a particular program, processor 50 may controlstimulation generator 60 to deliver stimulation according to theselected therapy program or programs in the groups, e.g., simultaneouslyor on a time-interleaved basis. A group may include a single therapyprogram or multiple therapy programs. As mentioned previously, eachprogram may specify a set of stimulation parameters, such as amplitude,pulse width and pulse rate, if applicable. For a continuous waveform,parameters may include amplitude and frequency. In addition, eachprogram may specify a particular electrode combination for delivery ofstimulation, and an electrode configuration in terms of the polaritiesand status of the electrodes. The electrode combination may specifyparticular electrodes in a single array or multiple arrays, and on asingle lead or among multiple leads.

Stimulation generator 60 is electrically coupled to electrodes 48A-48Pvia conductors 49 of the respective lead, such as lead 10 in FIG. 1, inimplementations in which electrodes 48A-48P are carried by (e.g.,located on) leads. As described above, in some examples, electrodes48A-48P can be carried by a common lead or by two or more separateleads. Thus, conductors 49 can be conductors of one or more leads.Stimulation generator 60 may be electrically coupled to one or morehousing (“can”) electrodes 48Q via an electrical conductor disposedwithin the housing of implantable stimulator 4 (FIG. 1) or implantablestimulator 34 (FIG. 3). A housing electrode 48Q may be configured as aregulated or unregulated electrode to form an electrode configuration inconjunction with one or more of electrodes 48A-48P located on leadscoupled to stimulator 34. For example, housing electrode 48Q may beconfigured for use as an anode to source current substantiallysimultaneously with one or more electrodes, e.g., any of electrodes48A-48P, on one or more leads configured for use as cathodes.

Stimulation generator 60 may include stimulation generation circuitry togenerate stimulation pulses or waveforms and circuitry for switchingstimulation across different electrode combinations, e.g., in responseto control by processor 50. Stimulation generator 60 produces anelectrical stimulation signal in accordance with a program based oncontrol signals from processor 50. Stimulation generator 60 can be asingle channel or multi-channel stimulation generator. For example,stimulation generator 60 may be capable of delivering a singlestimulation pulse, multiple stimulation pulses, or a continuous signalat a given time via a single electrode combination or multiplestimulation pulses at a given time via multiple electrode combinations.

In some examples, stimulation generator 60 may include a chargingcircuit that selectively applies energy from power source 54 to acapacitor module for generation and delivery of a supply voltage forgeneration of stimulation signal. In addition to capacitors, thecapacitor module may include switches. In this manner, the capacitormodule may be configurable, e.g., based on signals from processor 50, tostore a desired voltage for delivery of stimulation at a voltage orcurrent amplitude specified by a program. For delivery of stimulationpulses, switches within the capacitor module may control the widths ofthe pulses based on signals from processor 50.

Sensing module 58 may be configured to sense a physiological parameterof patient 6, such as a bioelectrical brain signal within brain 16(e.g., local field potentials (LPF) signals which include EEG and ECoGsignals, or a broader genus of electrical signals within brain 16) or ahemodynamic characteristic (e.g., blood pressure, blood volume, or bloodflow) within brain 16. Sensing module 58, under the control of processor50 (or a processor of another device, such as programmer 20 of FIG. 1),may sense bioelectrical signals or another signal indicative of apatient parameter and provide the sensed signals to processor 50. Tosense bioelectrical brain signals, processor 50 may control sensingmodule 58 to selectively sense bioelectrical brain signals withsub-combinations of electrodes 48A-48P. In this manner, stimulator 34may be configured such that sensing module 58 may sense bioelectricalsignals with different combinations of electrodes 48A-48P. Althoughsensing module 58 is incorporated into a common housing with stimulationgenerator 60 and processor 50 in the example shown in FIG. 2, in otherexamples, sensing module 58 may be in a physically separate housing fromstimulator 34 and may communicate with processor 50 via wired orwireless communication techniques. Sensing module 58 may receive thebioelectrical signals from electrodes 48A-48P or other electrodespositioned to monitor brain signals of patient 6. Processor 50 mayreceive the output of sensing module 58, which may be raw bioelectricalsignals. In other examples, processor 50 may apply additional processingto the bioelectrical signals, e.g., convert the signals to digitalvalues for further processing, filter the signals, and the like. In oneexample, sensing module 58 may be configured to sense hemodynamiccharacteristics (e.g., blood pressure, blood volume, or blood flow). Inthis example, sensing module 58 may include circuitry such as, forexample, a pressure sensor, a pulse oximeter, and the like for sensinghemodynamic characteristics.

Telemetry module 56 supports wireless communication between implantablestimulator 34 and an external programmer 20 and/or 22, or anothercomputing device under the control of processor 45. Telemetry module 56may include a RF transceiver to permit bi-directional communicationbetween implantable stimulator 34 and each of clinician programmer 20and patient programmer 22. In one example, telemetry module 56 mayutilize other communication protocols and a corresponding transceiver,for example, a Bluetooth® transceiver for telemetry using the Bluetooth®protocol. Telemetry module 56 may include an antenna 57 that may take ona variety of forms. For example, antenna 57 may be formed by aconductive coil or wire embedded in a housing associated with medicaldevice 4. Instead or in addition to the conductive coil or wire, antenna57 may be mounted on a circuit board carrying other components ofimplantable stimulator 34 or take the form of a circuit trace on thecircuit board. In this way, telemetry module 56 may permit communicationwith clinician programmer 20 and patient programmer 22 in FIG. 1, toreceive, for example, new programs or program groups, or adjustments toprograms or program groups.

Telemetry module 56 may also communicate information regarding previoustherapy sessions that have been stored in memory 52, to an externalprogrammer during a subsequent therapy session; the informationregarding a previous therapy session may have been imported by aprogrammer used in the previous session. The stored information mayinclude, for example, lead placement in the patient, stimulation therapyparameter values, desired therapy outcome defined by the user for aparticular program, patient information, clinic(s) where patient hadpreviously received treatments, previous clinician information, and thelike.

Power source 54 may be a non-rechargeable primary cell battery or arechargeable battery and may be coupled to power circuitry. However, thedisclosure is not limited to examples in which the power source is abattery. In another example, as an example, power source 54 may comprisea supercapacitor. In some examples, power source 54 may be rechargeablevia induction or ultrasonic energy transmission, and include anappropriate circuit for recovering transcutaneously received energy. Forexample, power source 54 may be coupled to a secondary coil and arectifier circuit for inductive energy transfer. In additional examples,power source 54 may include a small rechargeable circuit and a powergeneration circuit to produce the operating power. Recharging may beaccomplished through proximal inductive interaction between an externalcharger and an inductive charging coil within stimulator 34. In someexamples, power requirements may be small enough to allow stimulator 34to utilize patient motion at least in part and implement a kineticenergy-scavenging device to trickle charge a rechargeable battery. Avoltage regulator may generate one or more regulated voltages using thebattery power.

FIG. 3 is a functional block diagram illustrating various components ofan example external programmer 40 for an implantable stimulator 34.External programmer 40 is an example of clinician programmer 20 orpatient programmer 22 shown in FIG. 1. As shown in FIG. 3, externalprogrammer 40 includes processor 53, memory 55, telemetry module 67,user interface 59, and power source 61. In general, processor 53controls user interface 59 and receives user input via user interface59, stores and retrieves data to and from memory 55, and controlstransmission of data with implantable stimulator 34 through telemetrymodule 67. Processor 53 may take the form of one or moremicroprocessors, controllers, DSPs, ASICS, FPGAs, or equivalent discreteor integrated logic circuitry. The functions attributed to processor 53herein may be embodied as software, firmware, hardware or anycombination thereof.

Memory 55 may store instructions that cause processor 53 to providevarious aspects of the functionality ascribed to external programmer 40herein. Memory 55 may include any fixed or removable magnetic, optical,or electrical media, such as RAM, ROM, CD-ROM, magnetic disks, EEPROM,or the like. In some examples, memory 55 may also include a removablememory portion that may be used to provide memory updates or increasesin memory capacities. A removable memory may also allow patient data tobe easily transferred to another computing device, or to be removedbefore programmer 40 is used to program therapy for another patient.Memory 55 may also store information that controls operation ofimplantable stimulator 34, such as therapy delivery values. In someexamples, memory 55 may store therapy program information, which may betransferred to the stimulator 34.

User interface 59 may include a display screen and one or more inputbuttons that allow external programmer 40 to receive input from a user.The screen may be, for example, a liquid crystal display (LCD), lightemitting diode (LED) display, plasma display, dot matrix display, ortouch screen. The input buttons may include a touch pad, increase anddecrease buttons, emergency shut off button, and other input medianeeded to control the stimulation therapy. The input buttons may bededicated to performing a certain function, i.e., a power button, or thebuttons may be soft keys that change in function depending upon thesection of the user interface presented by the display of user interface59 currently viewed by the user.

A clinician or patient 6 interacts with user interface 59 in order to,for example, manually select, change, or modify therapy programs, e.g.,by adjusting voltage or current amplitude, adjusting pulse rate,adjusting pulse width, or selecting different electrode combinations orconfigurations, and may provide efficacy feedback or view stimulationdata via user interface 59. In some examples, user interface 59 displaysa model of a brain network associated with a condition of patient 6. Themodel may resemble a network diagram, and can graphically depictrepresentations of brain anatomical structures that are functionallyconnected, such that stimulation of one part of the brain network in onestructure may generate excitatory and/or inhibitory effects on one ormore other structures within the brain network. In one example,stimulation of one or more parts of the brain network may inducesynchronization or desynchronization between two or more brainsstructures.

In one example, the effects on the brain structures are associated withthe patient condition, e.g., a therapeutic outcome that includesminimizing or eliminating one or more symptoms of the patient condition.The user, e.g., a clinician, may use the input buttons (e.g., physicalbuttons of the user interface that can be depressed or otherwiseactivated by a user or buttons displayed on a touch-screen of the userinterface) of user interface 59 to specify a desired therapeutic outcomeof stimulation applied to the structures of the brain networkrepresented by the model, where the therapeutic outcome can includebeneficial therapeutic effects and/or stimulation-induced side effectsassociated with the patient condition. Processor 53 may then determinestimulation therapy parameter values that define a stimulation therapyprogram that may help achieve the desired therapeutic outcome indicatedby the patient when stimulator 34 delivers therapy to patient 6 inaccordance with the therapy program. In this manner, the user may beable to configure stimulation therapy parameter values by specifying thedesired therapeutic effect for the stimulation delivered by stimulator34.

Programmer 40 may communicate wirelessly with implantable stimulator 34via telemetry module 67, which may include an internal antenna and/or anexternal antenna. Telemetry module 67 can be configured to support thetransfer of data to and from stimulator 34. Telemetry module 67 maycommunicate automatically with stimulator 34 at a scheduled time or whenthe telemetry module detects the proximity of the stimulator.Alternatively, telemetry module 67 may communicate with stimulator 34when signaled by a user through user interface 59. To support RFcommunication, telemetry module 44 may include appropriate electroniccomponents, such as amplifiers, filters, mixers, encoders, decoders, andthe like. In other examples, telemetry module 67 may employ othercommunication standards such as, for example, Bluetooth® and telemetrymodule 67 may include the appropriate Bluetooth® components.

Programmer 40 may communicate wirelessly with implantable stimulator 34using, for example, RF communication or proximal inductive interactionor other communication standards such as, for example, Bluetooth®. Insome examples, telemetry module 67 may be similar to telemetry module 56(FIG. 2) of implantable stimulator 34. In accordance with thisdisclosure, programmer 40 may communicate stimulation parameter valuesdetermined based on a desired therapeutic outcome specified by the userto stimulator 34 via telemetry module 67. Additionally, programmer 40may access models of a brain network associated with a patient conditionand any previously-defined therapeutic outcomes for viewing andmanipulation by the user via user interface 59. Programmer 40 may alsoretrieve information regarding placement of leads in structuresassociated with the brain network model that the user is currentlyviewing. In some examples, patient 6 may be associated with one or morepatient conditions, and programmer 40 may retrieve information regardinga selected patient condition or all patient conditions.

Programmer 40 may also be configured to communicate with anothercomputing device via wireless communication techniques, or directcommunication through a wired, e.g., network, connection. Examples oflocal wireless communication techniques that may be employed tofacilitate communication between programmer 24 and another computingdevice include RF communication based on the 802.11 or Bluetooth®specification sets, infrared communication, e.g., based on the IrDAstandard.

Power source 61 delivers operating power to the components of programmer40. Power source 61 may be a rechargeable battery, such as a lithium ionor nickel metal hydride battery. Other rechargeable or conventionalbatteries may also be used. In some cases, external programmer 40 may beused when coupled to an alternating current (AC) outlet, i.e., AC linepower, either directly or via an AC/DC adapter. Power source 61 mayinclude circuitry to monitor power remaining within a battery. In thismanner, user interface 59 may provide a current battery level indicatoror low battery level indicator when the battery needs to be replaced orrecharged. In some cases, power source 61 may be capable of estimatingthe remaining time of operation using the current battery.

A user of programmer 40 may utilize user interface 59 to select one ormore stimulation parameter values for stimulation generated anddelivered by stimulator 34 by indicating a desired therapeutic outcome(e.g., a balance of beneficial therapeutic effects and/orstimulation-induced side effects) for a patient condition of patient 6.In response to receiving input indicating a desired therapeutic outcomefor a selected patient condition, processor 53 of programmer 40 selectsone or more therapy parameter values that may achieve the desiredtherapeutic outcome. The one or more therapy parameter values can definea therapy program.

In some examples, user interface 59 may display a model of a brainnetwork associated with the patient condition. In some examples, themodel represents a brain network diagram that includes graphicalrepresentations corresponding to brain structures affected by excitatoryand/or inhibitory stimulation, where applying stimulation to onestructure in the brain network has an excitatory and/or inhibitoryeffect on one or more other structures in the brain network. The usermay select the desired therapeutic outcome by adjusting the excitatoryand/or inhibitory impact on the structures in the brain networkrepresented by the model. Processor 53 may translate the user inputsinto stimulation therapy parameter values that result in the desiredtherapeutic outcome when applied by stimulator 34. In this manner, theuser may be able to select and configure stimulation therapy parametervalues by specifying the desired therapeutic effect of brain therapythat is delivered by stimulator 34 in accordance with this disclosure.

In some examples, programmer 40 can be configured to store a pluralityof different brain networks for respective patient conditions, such thatprocessor 53 can present, via user interface 59, a plurality of patientconditions for selection by a user.

FIGS. 4A-4C illustrate an example programmer graphical user interface(GUI) 102, which processor 53 may present to a user via a display ofuser interface 59 of programmer 40. As described above with respect toFIG. 3, in some examples, programmer 40 may be a clinician programmer 20(FIG. 1), while in other examples, programmer 40 may be a patientprogrammer 22. FIGS. 4A-4C illustrate an example user interface forprogramming stimulation therapy for of patient 6 receiving stimulationtherapy for a particular condition, such as, Parkinson's disease, as anillustrative example. The example model of FIG. 4B illustratesinhibitory and/or excitatory relationships and/or effects between therepresented brain structures. In other examples, models of brainnetworks associated with other diseases or conditions may illustrateother relationships and/or effects among the brain structures. In oneexample, a model of a brain network may indicatesynchronization/desynchronization relationships between brain structuresin epileptic syndromes, patterns of activation of brain structures(e.g., as indicated by a time domain or frequency domain characteristicof a bioelectrical brain signal or a signal indicative of hemodynamicactivity within the brain) in response to a stimulus such as an acute orchronic pain state. In addition, in other examples, a model of a brainnetwork may include anatomical structures of brain 16 that are relevantto psychiatric disorders, such as major depressive disorder (MDD),obsessive compulsive disorder (OCD), post traumatic stress disorder, ananxiety disorder, and the like. Other types of models that illustratebrain networks associated with other types of patient conditions arecontemplated.

In some examples, for a particular patient condition, a clinician maydetermine the structures of brain 16 that define a brain network by, forexample, utilizing a functional magnetic resonance image (fMRI) thatindicates neural activity (e.g., based on cerebral blood flow) in brain16 for particular patient conditions or specific patient statesassociated with the patient condition. The clinician may deliverstimulation to one structure of brain 16 (e.g., using a probe with anelectrode) and determine, based on the fMRI, what other structures ofbrain 16 are affected by the stimulation. This process may be repeatedfor any number of structures of brain 16. The group structures that aredetermined to be interrelated by at least one common anatomicalstructure, and affected by stimulation delivered to at least one otheranatomical structure in the group of structures may then define a brainnetwork.

As FIG. 4A illustrates, programmer 40 may present to the user, via GUI102, a list of conditions associated with the patient. In anotherexample, GUI 102 may display a general list of conditions that may notall be applicable to patient 6, and a user may select a condition orconditions specific to the patient from the general list. In oneexample, processor 53 of programmer 40 may retrieve the list ofconditions from IMD 34, from memory 55 of programmer 40, from a remotedatabase, or any other storage device associated with programmer 40 orwith which programmer 40 can communicate. If the list of patientconditions and, if applicable, associated models of brain networks arestored in another device, processor 53 may retrieve the list ofconditions using telemetry module 67 or by connecting directly to adatabase of patient data. In examples in which processor 53 retrievesthe list of conditions from a device other than programmer 40, processor53 may store the retrieved information in memory 55. In addition to thelist of conditions, processor 53 may retrieve or generate a model ofbrain network associated with each of the conditions. The model of abrain network for a patient condition may be retrieved when thecondition is selected by a user by interacting with GUI 102.

Models of brain networks may be unique to a specific patient conditionor may cover a variety of related conditions. In one example, models ofbrain networks may be created based on research (e.g., using the fMRItechnique described above) or known literature and stored as librariesin memory 55 of programmer 40. In another example, such libraries may bestored at a central repository accessible by programmer 40, andprocessor 53 of programmer 40 may retrieve libraries relevant to apatient condition from the central repository at time ofuse/programming. In some examples, the stored libraries may beperiodically updated based on the latest research or the latestclinician knowledge, such that at the time of retrieval by programmer40, the latest library for a given patient condition is available. Inother examples, processor 53 of programmer 40 or another device maygenerate or configure models of brain networks from a default model attime of implant or at the time of first programming based onphysiological sensing and patient-specific factors determined/generatedby clinical procedures, e.g., using the fMRI technique described above.

In the example of FIG. 4A, GUI 102 may list brain networks for aplurality of patient conditions, such as Parkinson's disease 105,dystonia 107, and epilepsy 109, which may be associated with patient 6or may be a general list of conditions not patient-specific. The usermay select a condition for which the user wishes to configure astimulation therapy program by interacting with GUI 102, e.g., clickingon the respective condition. Upon receiving the user input, processor 53of programmer 40 may present to the user GUI 102 via a display of userinterface 59 (FIG. 3), a model of a brain network associated with theselected patient condition. A brain network associated with a selectedcondition may include structures that are relevant to the condition, andlinks between the structures indicating the relationship between thestructures, where the relationship may be an indication of the effect ofone structure on another one or more structures. Abnormalities in brainfunction associated with a patient condition may result in generatingabnormal electrical activity or abnormal hemodynamic activity in certainstructures of brain 16. These structures may be used to generate a modelof a brain network that illustrates the functional relationship amongthe brain structures of the brain network. The structures of the brainnetwork may be structures where activity indicative of the presence orseverity of a condition is observed, or structures that affect functionsof other structures outside the brain network where activity isobserved.

The model of the brain network includes structures of brain 16 that areaffected by or that affect characteristics (e.g., symptoms) of thepatient condition. For example, a decrease in power in a given frequencyband (e.g., beta) may result in a decrease in a symptom state (e.g.,tremor in Parkinson's disease). Processor 53 of programmer 40 mayreceive user input via the user interface 59 indicating a desiredtherapeutic outcome of a therapy delivered to patient 6 by stimulator34. Processor 53 generates a stimulation therapy program based on userinput, by translating user input into stimulation parameter values thatthe IMD applies to produce the desired therapeutic outcome. In someexamples, such as when programmer 40 is used for more than one patientor upon initial set-up of patient-dedicated programmer 40, a user mayset up a profile for patient 6 and a programming session for patient 6prior to selecting a therapy program with the aid of GUI 102.

Programmer 40 may provide the user with options and selections via GUI102 that allow the user to select the implant location of one or moreleads 12 or the intended implant location of the leads if the leads havenot been implanted yet. The implant location can be, for example, thestructures in brain 16 in which leads 12 are located or structures thatan electrical field resulting from stimulation therapy may cover. In oneexample, the options and selections may include location (e.g., asindicated by stereotactic coordinates or another coordinate system) ofthe tip of a lead or its individual electrodes; location of at least oneof the tip of a lead or an electrode with orientation information (e.g.,angles of leads or electrodes relative to a known coordinate system)such that other coordinates can be determined; options with which theuser can directly specify location of the one or more leads on a postsurgical image; model numbers or physical dimensions of a given lead; aset of measured physiological signals associated with electrodes fromwhich location information can be inferred (e.g., the location of a leadcan be determined based on biomarkers); or other information relevant toestablishing the location of lead elements relative to brain structures.

In one example, the lead implant location information may be stored inIMD 4 or may be available from a previous programming session and storedin memory 55 of programmer 40. In one example, processor 53 may retrievelead implant information and automatically place lead icons 132 and 134on the brain structures in which they are implanted, based on leadlocation information available to programmer 40 or in IMD 4. In oneexample, programmer 40 may allow the user to access the lead implantlocation information. In other examples, the user may provide inputspecifying the lead implant location.

As FIG. 4B illustrates, programmer GUI 102 includes display screen 104,and selection buttons 114, 116, and 118. Display screen 104 may presentto the user options from which to select and go from one screen toanother. The user may use selection buttons 114, 116, and 118 to makeselections or otherwise provide input, and/or soft keys that GUI 102 maypresent to the user on display screen 104. In addition or in otherexamples, the user may interact with a touch screen to make selectionsand provide other types of input.

Lead implant information may be, for example, coordinates (e.g.,stereotactic coordinates or another three-dimensional coordinate system)relative to a known frame of reference for one or more lead elements(e.g., tip, electrode centers, or the like). In other examples, leadimplant information may be, for example, a coordinate in addition to aset of angles that may be used to determine other coordinates associatedwith the electrodes of the lead. In addition to or instead ofcoordinates, lead implant information may also be, for example,associations between lead elements (e.g., tip, electrodes, or the like)and anatomical structure boundaries within the brain. For example, leadimplant information may specify that a first electrode is wholly withina patient's left STN, a second electrode is partially within left STN, athird electrode is outside left STN, and the like.

In some examples, programmer 40 may be configured to receiveimage-driven information entry, such that the user may specify leadimplant location by placing lead graphics on an image of the brainpresented by GUI 102 or by registering lead elements to the image via aseries of user inputs (e.g., selecting lead elements by touching orclicking with a user input device each electrode on a lead image). Inone example, a subset of lead elements may be used to identify leadimplant location (e.g., a first and last electrode) where processor 53of programmer 40 may determine locations of other electrodes of the leadusing known dimensions and spacing of electrodes to interpolatelocations of electrodes based on identified locations of a subset ofelectrodes, for example. In this example, the user may be able to drag alead graphic to structures of the brain where the lead is implanted,rotate and apply curves to the lead graphic.

As part of the set up of GUI 102, processor 53 may allow the user tocalibrate the therapy system to obtain baseline information for theleads 12 and for structures of brain 16 affected by the stimulationtherapy (e.g., structures covered by an electrical field generated bythe delivery of stimulation by stimulation generator 34 via leads 12).During calibration and baseline-obtaining, processor 53 of programmer 40may determine, given placement of leads relative to one or moreanatomical structures of brain 16 and/or each other if multiple leadsare implanted within patient 6, the relationship between the effect onthe behavior of structures in the brain network and changes in therapyparameter values. For example, processor 53 may determine a relationshipbetween values of therapy parameters and the activity of the structure.For example, processor 53 may determine an electrode combination, andparameter values associated with the electrode combination (e.g., pulsewidth, pulse amplitude, and the like) that may cause an increase in theactivity of a brain structure when stimulation is applied to the brainstructure using the determined electrode combination and stimulationparameter values. In one example, the relationship between thestimulation parameter values and a brain structure may be determined byprocessor 53 (e.g., by controlling stimulator 34 to deliver stimulationaccording to the selected parameter values and then sensing activitywithin the brain structure during or immediately following the deliveryof stimulation). In another example, the relationship betweenstimulation parameter values and a brain structure may be known andstored, e.g., in memory 55.

In one example, the behavior of the brain structures may be expressed interms of the amount of inhibition or activation of one or more otherbrain structures. In one example, calibration may involve sensing and/orstimulating using each electrode to measure and/or elicit a response,then associate the response to an appropriate structure in the modelbrain network. For example, sensing a particular frequency band at oneelectrode may imply that the electrode is in a specific anatomicalstructure. In another example, stimulating an electrode to elicit agiven response may imply correlation of that electrode with a specificanatomical structure known to produce that response.

When the user completes setting up a current programmer session, GUI 102may display on display screen 104 a model of the brain networkassociated with the specified leads and patient condition. The brainnetwork model may include graphical representations of brain structurescorresponding to structures of the brain network, where the graphicalrepresentation of the brain structures may be images of the brainstructures or schematic representations of the brain structures. In oneexample, the graphical representations of the brain structures may bepositioned to represent their actual positions relative to one anotherin the brain, or may be positioned so that structures are placed nearstructures to which they are linked in the model. The brain structuresof the brain network may not be the entire brain structure, but a regionof a brain structure that makes up less than the entire brain structure.In one example, the user can interact with the structures of the brainnetwork model by changing inhibitory or excitatory effects of thestructures of the brain network. The model of the brain network mayresemble a network with elements representing brain structures affectedor associated with a selected patient condition. In one example, withinthe displayed model of the brain network, the brain structure may begraphically represented by network components, which are functionallyconnected with one another, and may have inhibitory and/or excitatoryeffects on other brain structures, as illustrated. When anatomicalstructures of brain 16 are functionally connected, a change in oneanatomical structure may affect one or more structures to which itconnects. In one example, the effect may be a sensed brain behavior oractivity.

The example of FIG. 4B is an example model of a brain network for braintherapy associated with Parkinson's tremor. In this example, the modelmay comprise cortex 106, striatum 108, subthalamic nucleus (STN) 112,and globus pallidus (GPe) 110. The graphical links, e.g., lines, betweenthese structures may indicate the relationship between structures. Therelationship may be, for example, the effect of stimulation in onestructure on the activity in one or more other structures. For example,in the example shown in FIG. 4B, the “+” may indicate an excitatoryeffect, and the “−” may indicate an inhibitory effect. For somestructures of the brain network displayed by GUI 102, there may be afeedback effect on the structure itself, e.g., a stimulation of astructure may cause an inhibitory or excitatory effect on the structureitself.

In the example of FIG. 4B, GUI 102 includes lead icons 132 and 134representing electrodes implanted in STN 112 and GPe 110. Lead icons 132and 134 may be schematic depictions of leads 12 and respectiveelectrodes 11 or may be images of leads 12 and respective electrodes 11(FIG. 1). The electrodes, their configuration, and the parameter valuesassociated with stimulation the electrodes deliver to brain 16, mayimpact the response of the structures, STN 112 and GPe 110, which mayimpact (e.g., alleviate or increase the severity) symptoms ofParkinson's disease, such as tremor. In one example, the implantedelectrodes may deliver electrical stimulation with certain stimulationparameter values to one or more portions of the brain network shown inFIG. 4B, which may cause the associated structure, e.g., the structureto which stimulation is delivered, to increase its excitatory effect onother structures. For example, a certain stimulation parameter valuesassociated with the electrodes implanted in STN 112, may have a certainexcitatory effect on GPe 110. Other configurations of the sameelectrodes may cause an increase in a structure's inhibitory effect.

In the example of FIG. 4B, the excitatory/inhibitory effects between thebrain structures are primarily bioelectrical activity (e.g., stimulationof one structure results in increasing/decreasing neural activity in alinked structure based on the relationship between them, i.e.,excitatory/inhibitory, respectively). In this example, stimulation ofSTN 112 may cause the electrical (or neural) activity in GPe 110 toincrease.

The GUI 102 may present the model of the brain network, and indicate anexisting relationship between the anatomical structures of the brainnetwork at an initial set of stimulation parameter values, and whetherthe user can change an effect of a certain structure on another oritself. For example, connection between cortex 106 and striatum 108 andother structures in this model show the effect on the other structuresby the “+” and “−” indications. However, processor 53 of programmer 40can configure GUI 102 such that the “+” and “−” indications may not behighlighted by selectable buttons, and, therefore, the user may not beable to directly change the effect cortex 106 and striatum 108 impose onother structures of the brain network shown in FIG. 4B.

As the user manipulates the intensity of stimulation applied tostructures in the brain network, such as STN 112 and GPe 110, theeffects on cortex 106 and striatum 108 may change accordingly. Theintensity of stimulation can be a function of, for example, theelectrodes used to deliver stimulation to brain 16, the current orvoltage amplitude of the stimulation signal, and other stimulationsignal parameters (e.g., frequency or, in the case of pulses, pulsewidth). In some examples, processor 53 can provide indications of theeffect structures have on other structures of the network or onthemselves, e.g., by presenting values within GUI 102 that reflect themagnitude of the impact of the structures on each other or on itself.The value of the magnitude of the impact may be a unitless number, butmay provide the user with an indication of the effect structures have onone another. For example, in the example shown in FIG. 4B, the magnitudeof impact on STN 112 is displayed as a unitless value 128. Similarly, inthe example shown in FIG. 4B, the magnitude of the impact of stimulationon GPe 110 may be displayed as a unitless value 130.

In one example, the magnitudes of impact may represent a measure of thesensed activity in the associated structure. In one example, themagnitudes of impact may be generated by comparing a sensed value of aphysiological parameter with a baseline value. The baseline value maybe, for example, measured during or soon after implant of leads 12 inbrain 16 and stored in memory 55 of programmer 22 or memory 52 of IMD34, a value measured in the absence of a stimulation state, or may be atheoretical value established by research or literature and simply usedas reference. The magnitude of impact may be expressed as a ratio (e.g.,sensed value/baseline value), as a percentage change (e.g., increase ordecrease relative to the baseline value), or as a magnitude of changefrom the baseline value (e.g., an absolute value of the increase ordecrease). In one example, the sensed activity may be a measure of afunction of the structure that is associated with the patient conditionor certain symptoms of the condition. The function may refer, forexample, to an electrical function of the structure (e.g., energy in aspectral band of a bioelectrical brain signal sensed in the structure,an action potential rate associated with the structure, and the like)that is known to correlate with a clinical outcome (e.g., symptom, sideeffect, and the like). In the example of FIG. 4B, for Parkinson'sdisease, the function of STN 112 may be a measure of energy in the betaband of a bioelectrical brain signal sensed within STN 112, which mayindicate the presence and/or the severity of tremor in a patient withParkinson's disease. For example, it is believed that abnormal activitywithin a beta band (e.g., about 8 hertz (Hz) to about 30 Hz or about 16Hz to about 30 Hz) of a bioelectrical brain signal is indicative ofbrain activity associated with a movement disorder (e.g., Parkinson'sdisease). In other examples, the function may refer to an amount ofblood flow out of or into a structure that is known to correlate with aclinical outcome.

In some examples, the connections between anatomical structures of abrain network may be configured such that stimulation delivered to oneanatomical structure can result in more or less synchronized activity(e.g., electrical activity or hemodynamic activity) with anotherstructure of the brain network, more or less power in a given spectralband (e.g., amount of energy present in a frequency band betweenspecified lower and upper frequency bounds as extracted using a Fouriertransform) relative to another brain structure or relative to abaseline, or other controllable effects of interest in the circuit. Themeasure of the sensed activity may be obtained by, for example, sensingbioelectrical brain signals with electrodes 48 of stimulator 34 in aunipolar or bipolar configuration, or determining hemodynamic activity(e.g., blood pressure or blood flow or volume) with leads 12 which caninclude a pressure sensor or a pulse oximeter. Sensing module 58 (FIG.2) of stimulator 34 or another sensing module may be used to sense thephysiological parameter and processor 53 may determine the sensedactivity based on a signal generated by sensing module 58.

Referring to FIG. 4B, the user may interact with GUI 102 to adjust andmanipulate the effects of stimulation applied to certain brain structurein the illustrated model network. In the example shown in FIG. 4B, theuser may adjust the effects of each of STN 112 and GPe 110 on oneanother by selecting buttons 124 and 126, where the “+” button 124 mayindicate an excitatory effect and the “−” button 126 may indicate aninhibitory effect. For example, a user input that increases anexcitatory effect to a given structure may cause a change in the sensedlevel of activity (e.g., bioelectrical brain signal amplitude or powerlevel within one or more frequency bands or hemodynamic activity) inthat structure. Processor 53 of programmer 40 may determine the therapyparameter values that would result in the change to the excitation ofthe brain structure indicated by the user.

Processor 53 may then apply the determined therapy parameter values andmeasure the sensed activity in the structures indicated by the user. Ifthe sensed level of activity does not change as expected based on theuser input, the system may indicate to the user that there is amismatch. In one example, if a mismatch is indicated, processor 53 mayattempt the requested change (e.g., the increased excitatory effect tothe structure) using a different set of parameters than the parametersinitially used. In other examples, if the sensed level does not changeas expected based on user input, the system may propose adjustments tothe network model (e.g., make links stronger or weaker, change linksfrom excitatory to inhibitory, or change the location of a lead relativeto structures to more accurately reflect changes made to stimulation).In one example, the system may adjust the strength of the links bymaking a link stronger or weaker. The strength of a link betweenstructures may indicate a gain associated with the link between thestructures, which can be used to predict activity in one structure basedon activity in another structure with which it links. In the example ofFIG. 4B, stimulation of STN 112 increases the activity in GPe 110, andthe amount of increase depends, among other factors, on the strength ofthe link between STN 112 and GPe 110. In one example, if the sensedlevel of activity in GPe 110 does not change as expected based on userinput, the system may propose adjusting the strength of the link betweenSTN 112 and GPe 110 by making it stronger, for example. Making the linkstronger may increase the gain associated with the link, and as aresult, stimulation of STN 112 at the same level as previouslyattempted, may result in a higher level of sensed activity in GPe 110.

In the example shown in FIG. 4B, the user may also adjust the effects ofeach of STN 112 on itself and GPe 110 on itself using the buttons 120and 122, respectively. In one example, the effects of stimulationdelivered to the brain network shown in FIG. 4B on each of STN 112 andGPe 110 may be represented using a value, instead of or in addition to“+” and “−” signs, where increasing or decreasing the effect isdisplayed as a number, e.g., percentage of a maximum value. STN 112 andGPe 110 may each be associated with implanted electrodes as illustrated,which may provide an indication of sensed activity in these structures.In one example, the sensed activity may be a bioelectrical brain signal,e.g., EEG, ECoG, a local field potential (LFP) reflecting activity of apopulation of neurons, a single neuron's spike train via amicroelectrode, or the like. The sensed activity may be indicated usinga value, as shown in the boxes with numbers inside each of thestructures, where the value reflects the magnitude of the impact of thestructures on each other or on itself, and may be expressed using aunitless number. In other examples, the value representing the sensedactivity may be a direct measure of the power in a band of interest,e.g., beta, gamma, alpha, etc., or degree of synchronicity of thebioelectrical brain signal associated with the structure, time domaincharacteristics of a bioelectrical brain signal (e.g., a mean, median,peak or lowest amplitude, instantaneous amplitude, pulse frequency orpulse to pulse variability), frequency domain characteristics of abioelectrical brain signal (e.g., an energy level in one or morefrequency bands), or some other measurable characteristic of a sensedphysiological signal, which may be sensed within brain 16

As the user interacts with the network displayed in GUI 102 and adjuststhe stimulation effects by, for example, selecting the icons with “+”and “−” signs, processor 53 dynamically adjusts the stimulationparameters based on the user input. For example, processor 53 may adjustthe stimulation parameters to values that help achieve the desiredstimulation effects. The effect of therapy delivered by stimulator 24that the user indicates by interacting with GUI 102 may change theactivity (e.g., electrical brain signal activity or hemodynamicactivity) sensed in each of the affected structures. The user maydetermine based on the changes in the sensed activity whether theadjustments are resulting in the desired effect. For example, the sensedactivity may be a measure of the power in a band of interest, and adecrease in sensed activity (e.g., power in a beta frequency band of asensed bioelectrical brain signal) may be known to correlate to adecrease in a symptom state (e.g., tremor).

As the user adjusts the effects of stimulation therapy on structures ofbrain 16, processor 53 can adjust the parameter values (e.g., electrodecombinations and configurations, stimulation signal amplitude,stimulation signal frequency, and the like) accordingly. Processor 53may use a mapping algorithm to determine the stimulation parametervalues, e.g., lead configuration, pulse width and rate, amplitude, etc.,that will yield the outcome or effect specified by the user. In oneexample, processor 53, when implementing the mapping algorithm, maycontrol stimulation generator 60 of stimulator 34 (FIG. 2) to applystimulation to each electrode 48 in sequence. Processor 53 may thenobtain objective measures of outcome, e.g., beneficial therapeuticeffects or stimulation-induced side effects at various stimulationamplitudes. The objective measures of outcome from the stimulationdelivery can be determined, e.g., based on a physiological parameter(e.g., a bioelectrical brain signal or a hemodynamic parameter) sensedby a sensing module of stimulator 34 or another sensing module that maybe physically separate from stimulator 34.

Processor 53, when implementing the mapping algorithm (which can bestored as instructions executable by processor 53), may store theobtained measures of the outcome of stimulation delivery andsubsequently use them to propose new stimulation settings given desiredoutcomes by reverse association and/or interpolation. In some examples,the mapping between the high level network effects, e.g., useradjustments to effects between structures of a brain network may beperformed using heuristics or guidelines associated with the network.For example, prior testing by a clinician or computer modeling canindicate that certain frequencies of stimulation may have a given effecton certain structures, and after the user specifies a desiredtherapeutic outcome, the adjusted effect is mapped to a correspondingfrequency. In either example, the user may adjust the effects of thestructures and the stimulation therapy, without having to directlyconfigure any stimulation parameters at a lower level.

Mapping of stimulation parameter values to particular effects of therapydelivered stimulator 34 may be configured as to provide an efficientcombination of therapy parameter values that yield the desired effect.For example, processor 53 may propose settings that achieve a givendesired outcome in a specific order (e.g., least energy consumingsettings to most energy consuming settings) for trial with patient 6. Inthis example, the least energy consuming settings may correspond tostimulation with lower intensity (e.g., lower frequencies, smaller pulsewidths, lower amplitudes, and/or fewer active electrodes). Whilemultiple therapy programs may help achieve a user-indicated effect oftherapy, processor 53 may select the therapy program that provides themost efficient usage of power.

In one example, the user may wish to see how adjusting effects ofstructures, e.g., stimulating one structure to generate a desired sensedactivity in another structure in the network influences theconfiguration of the stimulation parameters (e.g., the stimulationparameter values). GUI 102 may provide the user with button 114, theselection of which may present a user interface that presents details ofthe medical device programming at a lower level, e.g., visualization oftissue effects (e.g., volume of tissue activated, an electrical fieldthat represents structures of brain 16 that will be covered by anelectrical field generated by the delivery of electrical stimulation, ora voltage gradient or a current density model that indicates the voltagegradient or current density of the electrical field) or stimulationsettings and parameter values. In one example, GUI 102 may provide asplit screen option for the user to see both the higher level modelnetwork interactive screen 104, and the stimulation parameter values. Inthis example, as the user changes effects between structures in themodel network, the user can see the corresponding changes in stimulationparameter values to achieve the desired effect as indicated by the user.

In the examples using the model of brain network, the user may have anunderstanding of the effect each structure's sensed activity has on thepatient condition, e.g., the relationship between the sensed activity inSTN and the amount of tremor experienced by a patient. For example, theuser may understand how the activity level in STN affects an outcome,e.g., right arm tremor, and/or a side effect, e.g., transientparesthesia. As illustrated in FIG. 4C, in one example, GUI 102 mayprovide the user with a higher level of visualization and programming,and allow the user to specify a balance between the therapeutic benefitsoutcome and stimulation-induced side effects. In this example, GUI 102may display on display screen 104, a list of symptoms and side effectsassociated with a condition, e.g., tremor 121 and transient parasthesia123 in the example shown in FIG. 4C. The user may selectively increaseor decrease the therapeutic outcomes and side effects. For example, theuser may indicate a desired outcome of 50% less tremor and 75% lesstransient paresthesia. These percentages may be relative to a baselinepatient state in no symptoms of the patient condition with which patient6 is afflicted are present, or a patient state specific to patient 6 inwhich the patient symptoms were reduced and/or the stimulation-inducedside effects were minimized or even eliminated.

Upon receiving user input indicating the desired relative levels oftherapeutic benefits outcome and stimulation-induced side effects,processor 53 of programmer 40 may determine adjustments to thestimulation settings based on the brain network associated with thepatient condition by increasing or decreasing excitation or inhibitionof adjustable structures, e.g., STN 112 and GPe 110, in the exampleshown in FIG. 4B. In one example, processor 53 may determine adjustmentsto brain network (e.g., relative levels of excitation or inhibition ofthe anatomical structures) by using relationships established in aprevious mapping of the anatomical structures to outcomes, or by usingrelationships established by previous research efforts or available inthe literature (e.g., knowledge that stimulation of STN decreasestremor). Processor 53 may determine adjustments to the stimulationparameter values based on understandings of the propagation ofelectrical energy in brain tissue (e.g., knowledge that stimulation ofSTN decreases tremor, and that to further decrease tremor the STN mustbe stimulated at a higher amplitude than previously attempted).Processor 53 may also translate the adjustments in the brain networkinto changes in programming parameter values applied to specificelectrodes, as determined and optimized by the mapping algorithm.

In one example, the user may wish to revert to the default settings torestart the programming process, and may select button 116 labeled“clear” to return to the default setting before the user started makingany changes. In one example, the default settings may be the stimulationparameter values from the most recent programming session. In anotherexample, the default settings may be the stimulation parameter valuesbelieved to be effective for some patients with the same condition asthe patient. Once the user finishes making changes and adjustments, theuser may select button 118 labeled “program” to program stimulator 34using the adjusted program settings. Processor 53 of programmer 40causes the transmission of the adjusted therapy program to stimulator 34via the respective telemetry modules 67, 56, and processor 50 ofstimulator 34 may receive the adjusted therapy program and controlstimulation generator 60 to generate and deliver stimulation to patient6 based on the adjusted therapy program.

As previously described, processor 53 of programmer 40 can control userinterface 59 to display a model of a brain network associated withpatient conditions other than movement disorders, receive user input viathe model indicating a desired effect of therapy, and determine one ormore stimulation parameter values based on the user input. In someexamples, the brain network includes one or more anatomical structures(or regions of an anatomical structure) that affect or are affected bysymptoms of the patient condition. FIG. 5 illustrates an example model500 of a brain network associated with epilepsy. In the example shown inFIG. 5, model 500 of the brain network associated with epilepsy includeslateral thalamus 502, medial thalamus 504, sub thalamus 506, midbraintegmentum 508, pons 510, hypothalamus 512, substantia nigra 514, frontallobe 516, parietal lobe 518, basal ganglia 520, lateral temporal lobe522, and mesial temporal lobe 524, which are anatomical structures ofbrain 16 of patient 6 that may be affected or have an effect on apatient with epilepsy. In the example of FIG. 5, the effects betweenstructures may correspond to positive and negative correlations betweenthe structures, where delivery of electrical stimulation that increasescerebral blood flow (CBF) in one structure may increase or decrease CBFin another structure of the network. A positive correlation may beindicated by a solid connection between structures and indicates that anincrease/decrease in CBF in one structure causes an increase/decrease inCBF in a connected structure, and a negative correlation may beindicated by a dotted connection (e.g., connections 511 and 513) betweenstructures and indicates that an increase/decrease in CBF in onestructure causes a decrease/increase in CBF in a connected structure.

FIG. 6 is a flow diagram of an example technique for programming amedical device by generating a user interface that presents a model of abrain network, and selecting stimulation parameter values based on userinput provided via the user interface. A programmer, e.g., programmer40, receives user input via user interface 59 to initiate programming ofa stimulation program for delivering therapy to a patient, where theuser input indicates lead placement and patient condition (202). In someexamples, processor 53 may present to the user a list of conditionsassociated with the patient, and the user may select the condition forwhich the user wishes to configure the stimulation therapy program.

Thus, in some examples, the user input may indicate the lead placementand the patient condition for which the user is programming thestimulation therapy. In one example, processor 53 may retrieve leadplacement information stored in memory 55 (FIG. 2) from a previoussession or at time of implant. The lead placement information mayinclude, for example, coordinates in three-dimensional space ofelectrodes of the leads (e.g., stereotactic coordinates).

As part of the set up of a programming session, programmer 53 maypresent a user interface via user interface 59 to the user that permitsthe user calibrate the therapy system to obtain baseline information forthe leads implanted in patient 6 and for brain structures affected bythe stimulation therapy. In one example, calibrating the system mayinclude stimulating electrodes expected to yield a given therapeuticeffect, and then sensing a physiological signal (e.g., a bioelectricalbrain signal or a signal indicative of a hemodynamic characteristic) ofpatient 6 to determine whether the stimulation delivery actuallyelicited the effect (e.g., inhibition or excitation of electricalactivity). The sensed information may be subsequently used to refine thedetermination of stimulation parameter values given a user-indicateddesired effect on a brain structure or outcome (e.g., eliminating orminimizing tremor). During calibration and baseline-obtaining, processor53 of programmer 40 may determine, given placement of leads, therelationship between the effect on the behavior of structures in thebrain network and changes in stimulation parameter values. In oneexample, the behavior of the structures may be expressed in terms of theamount of inhibition or activation of a certain structure.

Programmer 40 may display, via user interface 59, a model of the brainnetwork associated with the specified leads and conditions (204). Insome examples, the brain network model may include graphicalrepresentations of anatomical brain structures with which the user mayinteract by changing applied stimulation that affects the inhibitory orexcitatory effects on that brain structure. In other examples, the brainnetwork model may include graphical representations of anatomical rainstructures with which the user may interact by changing appliedstimulation to change the synchronization or desynchronization ofelectrical activity within the brain structures.

The model of the brain network may resemble a network with elementsrepresenting brain structures affected or associated with a patientcondition. The structures may be functionally connected with each other,and the stimulation of one structure may have inhibitory and/orexcitatory effects on another structure within the network. In theexample shown in FIG. 6, processor 53 of programmer 40 may receive userinput via user interface 59 that indicates one or more adjustments tothe inhibition or excitation of one or more structures of the brainnetwork displayed by user interface 59 (206). The adjustments mayreflect increasing or decreasing the inhibitory and/or excitatory effectof adjustable structures on other structures.

Processor 53 can control user interface 59 to display an indication ofthe changes in the sensed activity at the structures of the brainnetwork as the user adjusts the effects of the structures (208). In someexamples, user interface 59 may indicate the sensed activity using aunitless value. In other examples, the value may be a direct measure ofthe power in a band of interest of a bioelectrical brain signal, e.g.,beta, gamma, alpha, etc., or degree of synchronicity of the signal withanother bioelectrical brain signal (e.g., sensed at another part of thebrain network), or some other measurable characteristic of the signal.As the user utilizes user interface 59 to interact with the brainnetwork and adjust the effects of the structures, processor 53 may causethe execution of instructions in accordance with the mapping algorithmsstored in memory 55 to dynamically adjust the stimulation parametervalues to values at which the user-indicated desired effect of therapymay be achieved (210).

In some examples, memory 55 of programmer 40 or a memory of anotherdevice (e.g., stimulator 34 or a remote database) may associate aneffect of therapy with a therapy parameter value or a change to atherapy parameter value. For example, memory 55 may store a particularexcitation level (e.g., as indicated by the unitless value displayed byGUI 102 or by a particular bioelectrical brain signal characteristic ora hemodynamic characteristic) of STN 112 and associate the excitationlevel with a particular stimulation parameter value (e.g., a frequencyvalue, a current or voltage amplitude, or pulse width if stimulator 34delivers stimulation signals in the form of pulses) or a therapy programthat defines values for each of a plurality of stimulation parameters.As another example, memory 55 may associate a particular percentage ofsynchronization of bioelectrical brain signal activity in STN 112 andGPe 110 with one stimulation parameter value or a therapy program thatdefines values for each of a plurality of stimulation parameters. Insome examples, processor 53 may adjust the stimulation parameter valuesto values based on the user input indicating a desired effect of therapydelivery by stimulator 34 by accessing a data structure within memory 55to determine which one or more stimulation parameter values areassociated with the therapeutic effect indicate by the user.

In some examples, processor 53 implements a mapping algorithm, which maybe stored in memory 55 (FIG. 3) to perform computations to configure thestimulation parameters, e.g., lead configuration, pulse width and rate,amplitude, etc., that will yield the outcome or effect specified by theuser. In some examples, the mapping between the high level networkeffects, e.g., user adjustments to effects between structures may beperformed using heuristics or guidelines associated with the brainnetwork. In some examples, processor 53 may utilize the mappingalgorithm to provide an efficient combination of programming parametervalues that yield the desired effect. For example, certain frequenciesof stimulation may have a given effect on certain structures, and as theuser specifies a desired effect of stimulation therapy, the adjustedeffect is mapped to a corresponding frequency. In either example, theuser may adjust the effects of stimulation on the structures of thebrain network and the stimulation therapy without having to directlyconfigure any stimulation parameters at a lower level.

In some examples, stimulator 34 includes a sensing module that isconfigured to sense a physiological parameter of patient 6, such as abioelectrical brain signal within brain 16 or a hemodynamiccharacteristic (e.g., blood pressure, blood volume or blood flow) withinbrain 16. In other examples, a sensing module separate from stimulator34 may sense the physiological parameter to determine a sensed activityvalue in the affected structures. Processor 53 may receive the rawsensed physiological signal waveform, a parameterized signal waveforms,or any other data other than the raw signal waveform, and determinewhether the sensed physiological signal indicates the adjustments to thestimulation parameters resulted in the desired therapeutic effect (e.g.,outcome) (212). For example, the sensed physiological parameter may be ameasure of the power in a band of interest, and a decrease in the sensedphysiological parameter (e.g., power in a beta frequency band of asensed bioelectrical brain signal) may be known to correlate to adecrease in a symptom state (e.g., tremor). Therefore, in the example ofParkinson's disease, if the desired outcome is a decrease in tremor,processor 53 may evaluate the effectiveness of a stimulation based onthe amount of decrease of power in the beta frequency band of abioelectrical brain signal. If the desired therapeutic effect is notachieved, processor 53 may readjust one or more of the stimulationparameter values (210) using values that may result in the desiredoutcome.

Processor 53 may iteratively repeat the determination whether thedesired outcome is achieved (212) and adjustment of the stimulationparameter values (210), until there is an indication that the adjustedparameters achieve the desired outcome. In this manner, the mappingalgorithm may adjust the model and parameter value predictions utilizingtechniques such as, for example, regression learning, trial and error,analytical approaches (e.g., solving a system of equations), finiteelement techniques, or the like. In one example, when processor 53determines or receives an indication that the desired outcome isachieved, processor 53 transmits, using telemetry module 67, the programparameters to IMD 4 (214), which may apply stimulation therapy accordingto the received program. In other examples, processor 53 may store theprogram parameters in memory 55 or may transmit the program parametersto a database. The processor may also transmit the program parameters toa remote program or system for trial stimulation. In some examples,processor 53 may store the program parameters as a starting point forfuture programming for the associated model.

While the techniques of this disclosure are described in the context ofbrain neural network activity, it should be understood that thetechniques of this disclosure are applicable to functions of otheranatomical structure and organs in the body. For example, cardiacfunctions may be monitored using techniques of this disclosure todetermine occurrence of events such as, for example, arrhythmias. In oneexample, functions of the heart may be monitored and may result in astable oscillatory trajectory, e.g., the plot of the monitored signalresembles an identifiable shape or circle back to the starting point.Trajectory changes may be a move to non-oscillatory state indicating,for example, an increase in frequency, which may indicate occurrence offibrillation of the heart. Based on this determination, the system maybe moved from the non-oscillatory state to the oscillatory state torestore the heart function to a normal state.

The techniques described in this disclosure, including those attributedto programmer 40, IMD 34 or various constituent components, may beimplemented, at least in part, in hardware, software, firmware or anycombination thereof. For example, various aspects of the techniques maybe implemented within one or more processors, including one or moremicroprocessors, DSPs, ASICs, FPGAs, or any other equivalent integratedor discrete logic circuitry, as well as any combinations of suchcomponents, embodied in programmers, such as physician or patientprogrammers, stimulators, image processing devices or other devices. Theterm “processor” or “processing circuitry” may generally refer to any ofthe foregoing logic circuitry, alone or in combination with other logiccircuitry, or any other equivalent circuitry.

Such hardware, software, firmware may be implemented within the samedevice or within separate devices to support the various operations andfunctions described in this disclosure. While the techniques describedherein are primarily described as being performed by processor 50 of IMD34 and/or processor 53 of programmer 40, any one or more parts of thetechniques described herein may be implemented by a processor of one ofIMD 34, programmer 40, or another computing device, alone or incombination with each other.

In addition, any of the described units, modules or components may beimplemented together or separately as discrete but interoperable logicdevices. Depiction of different features as modules or units is intendedto highlight different functional aspects and does not necessarily implythat such modules or units must be realized by separate hardware orsoftware components. Rather, functionality associated with one or moremodules or units may be performed by separate hardware or softwarecomponents, or integrated within common or separate hardware or softwarecomponents.

When implemented in software, the functionality ascribed to the systems,devices and techniques described in this disclosure may be embodied asinstructions on a computer-readable medium such as RAM, ROM, NVRAM,EEPROM, FLASH memory, magnetic data storage media, optical data storagemedia, or the like. The instructions may be executed to support one ormore aspects of the functionality described in this disclosure.

Various examples of the disclosure have been described. These and otherexamples are within the scope of the following claims.

1. A method comprising: displaying, on a user interface of a computingdevice, a graphical representation of a model of a network ofinterconnected anatomical structures of a patient, wherein the graphicalrepresentation of the network includes graphical links indicatingfunctional relationships between the anatomical structures; receivinguser input via the user interface specifying at least one effect oftherapy delivered by an implantable medical device to at least one ofthe anatomical structures of the patient; and determining, with aprocessor, one or more therapy parameter values with which theimplantable medical device generates therapy based on the user input andthe functional relationships between the anatomical structures.
 2. Themethod of claim 1, wherein determining the one or more therapy parametervalues comprises: determining a relationship between one or more therapyparameters and at least one of the anatomical structures; anddetermining the one or more therapy parameter values based on therelationship between the one or more therapy parameters and theanatomical structures.
 3. The method of claim 1, wherein determining theone or more therapy parameter values comprises determining one or moretherapy parameter values associated with the at least one effect oftherapy in a memory of a device.
 4. The method of claim 1, furthercomprising: delivering the therapy to the at least one of the anatomicalstructures; sensing a physiological parameter of the patient;determining whether the physiological parameter indicates the at leastone effect of therapy specified by the user input; and adjusting the oneor more therapy parameter values if the physiological parameter does notindicate the at least one effect of therapy specified by the user input.5. The method of claim 1, wherein the at least one effect indicates atleast one of an excitatory effect or an inhibitory effect on at leastone of the anatomical structures.
 6. The method of claim 1, wherein theat least one effect indicates at least one of a synchronization ordesynchronization between at least two of the anatomical structures. 7.The method of claim 1, further comprising displaying one or moreoutcomes associated with a patient condition, wherein the at least oneeffect indicates a desired change to the one or more outcomes.
 8. Themethod of claim 7, wherein the one or more outcomes includes at leastone of at least one beneficial therapeutic effect and at least onestimulation-induced side effect.
 9. The method of claim 1, wherein theimplantable medical device includes an electrical stimulator, and thetherapy parameter values define the electrical stimulation delivered bythe electrical stimulator to at least one of the anatomical structures.10. The method of claim 1, further comprising: displaying, on the userinterface, one or more patient conditions; receiving user input, via theuser interface, selecting a patient condition from the one or morepatient conditions; and selecting the graphical representation of thenetwork of interconnected anatomical structures based on the selectedpatient condition.
 11. The method of claim 1, further comprisingtransmitting the one or more determined therapy parameter values to theimplantable medical device.
 12. A system comprising: a user interfacethat displays a graphical representation of a model of a network ofinterconnected anatomical structures of a patient, wherein the graphicalrepresentation of the network includes graphical links indicatingfunctional relationships between the anatomical structures, wherein theuser interface is configured to receive user input specifying at leastone effect of therapy delivered by an implantable medical device to atleast one of the anatomical structures of the patient; and a processorthat determines one or more therapy parameter values with which theimplantable medical device generates therapy based on the user input andthe functional relationships between the anatomical structures.
 13. Thesystem of claim 12, wherein to determine the one or more therapyparameter values, the processor: determines a relationship between oneor more therapy parameters and at least one of the anatomicalstructures; and determines the one or more therapy parameter valuesbased on the relationship between the one or more therapy parameters andthe anatomical structures.
 14. The system of claim 12, wherein todetermine the one or more therapy parameter values, the processordetermines one or more therapy parameter values associated with the atleast one effect of therapy in a memory of a device.
 15. The system ofclaim 12, further comprising: a stimulation generator configured todeliver the therapy to the at least one of the anatomical structures;and a sensor configured to sense a physiological parameter of thepatient, wherein the processor determines whether the physiologicalparameter indicates the at least one effect of therapy specified by theuser input, wherein the processor adjusts the one or more therapyparameter values if the physiological parameter does not indicate the atleast one effect of therapy specified by the user input.
 16. The systemof claim 12, wherein the user interface displays one or more outcomesassociated with a patient condition, wherein the at least one effectindicates a desired change to the one or more outcomes.
 17. The systemof claim 16, wherein the one or more outcomes includes at least one ofat least one beneficial therapeutic effect and at least onestimulation-induced side effect.
 18. The system of claim 12, wherein theuser interface: displays, on the user interface, one or more patientconditions; receives user input, via the user interface, selecting apatient condition from the one or more patient conditions; and selectsthe graphical representation of the network of interconnected anatomicalstructures based on the selected patient condition.
 19. The system ofclaim 12, further comprising a telemetry device that is configured totransmit the one or more determined therapy parameter values to theimplantable medical device.
 20. The system of claim 12, furthercomprising a programmer for the implantable medical device, wherein theprogrammer comprises the user interface and the processor.
 21. A systemcomprising: means for displaying a graphical representation of a modelof a network of interconnected anatomical structures of a patient,wherein the graphical representation of the network includes graphicallinks indicating functional relationships between the anatomicalstructures; means for receiving user input specifying at least oneeffect of therapy delivered by an implantable medical device to at leastone of the anatomical structures of the patient; and means fordetermining one or more therapy parameter values with which theimplantable medical device generates therapy based on the user input andthe functional relationships between the anatomical structures.
 22. Thesystem of claim 21, wherein the means for determining the one or moretherapy parameter values comprises: means for determining a relationshipbetween one or more therapy parameters and at least one of theanatomical structures; and means for determining the one or more therapyparameter values based on the relationship between the one or moretherapy parameters and the anatomical structures.
 23. The system ofclaim 21, wherein the means for determining the one or more therapyparameter values comprises means for determining one or more therapyparameter values associated with the at least one effect of therapy in amemory of a device.
 24. The system of claim 21, further comprising:means for delivering the therapy to the at least one of the anatomicalstructures; means for sensing a physiological parameter of the patient;means for determining whether the physiological parameter indicates theat least one effect of therapy specified by the user input; and meansfor adjusting the one or more therapy parameter values if thephysiological parameter does not indicate the at least one effect oftherapy specified by the user input.
 25. The system of claim 21, furthercomprising means for displaying an indication of a function of the atleast one of the structures in response to the user input.
 26. Thesystem of claim 21, further comprising means for displaying one or moreoutcomes associated with a patient condition, wherein the at least oneeffect indicates a desired change to the one or more outcomes.
 27. Thesystem of claim 21, further comprising: means for displaying one or morepatient conditions; means for receiving user input selecting a patientcondition from the one or more patient conditions; and means forselecting the graphical representation of the network of interconnectedanatomical structures based on the selected patient condition.
 28. Anarticle of manufacture comprising a non-transitory computer-readablemedium comprising instructions that, upon execution, cause a processorto: display, on a user interface of a computing device, a graphicalrepresentation of a model of a network of interconnected anatomicalstructures of a patient, wherein the graphical representation of thenetwork includes graphical links indicating functional relationshipsbetween the anatomical structures; receive user input via the userinterface specifying at least one effect of therapy delivered by animplantable medical device to at least one of the anatomical structuresof the patient; and determine one or more therapy parameter values withwhich the implantable medical device generates therapy based on the userinput and the functional relationships between the anatomicalstructures.
 29. The computer-readable medium of claim 28, wherein theinstructions to determine the one or more therapy parameter valuescomprise instructions to: determine a relationship between one or moretherapy parameters and at least one of the anatomical structures; anddetermine the one or more therapy parameter values based on therelationship between the one or more therapy parameters and theanatomical structures.
 30. The computer-readable medium of claim 28,wherein the instructions to determine the one or more parameter valuescomprises instructions to determine a therapy parameter value associatedwith the at least one effect of therapy in a memory of a device.
 31. Thecomputer-readable medium of claim 28, further comprising instructionsto: deliver the therapy to the at least one of the anatomicalstructures; sense a physiological parameter of the patient; determinewhether the physiological parameter indicates the at least one effect oftherapy specified by the user input; and adjust the one or more therapyparameter values if the physiological parameter does not indicate the atleast one effect of therapy specified by the user input.
 32. Thecomputer-readable medium of claim 28, further comprising instruction todisplay, via the user interface, an indication of a function of the atleast one of the structures in response to the user input.
 33. Thecomputer-readable medium of claim 28, further comprising instructions todisplay one or more outcomes associated with a patient condition,wherein the at least one effect indicates a desired change to the one ormore outcomes.
 34. The computer-readable medium of claim 28, furthercomprising instructions to: display, on the user interface, one or morepatient conditions; receive user input, via the user interface,selecting a patient condition from the one or more patient conditions;and select the graphical representation of the network of interconnectedanatomical structures based on the selected patient condition.